AMD EPYC 7601 2P 2021

2 x AMD EPYC 7601 32-Core testing with a Dell 02MJ3T (1.2.5 BIOS) and llvmpipe on Ubuntu 19.10 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2101214-HA-AMDEPYC7645
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Audio Encoding 4 Tests
AV1 2 Tests
BLAS (Basic Linear Algebra Sub-Routine) Tests 2 Tests
C++ Boost Tests 2 Tests
C/C++ Compiler Tests 2 Tests
CPU Massive 5 Tests
Creator Workloads 10 Tests
Encoding 6 Tests
Fortran Tests 3 Tests
Game Development 2 Tests
HPC - High Performance Computing 13 Tests
LAPACK (Linear Algebra Pack) Tests 2 Tests
Machine Learning 4 Tests
Molecular Dynamics 4 Tests
MPI Benchmarks 2 Tests
Multi-Core 5 Tests
OpenMPI Tests 8 Tests
Programmer / Developer System Benchmarks 3 Tests
Python Tests 2 Tests
Scientific Computing 8 Tests
Server CPU Tests 2 Tests
Video Encoding 2 Tests

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January 19 2021
  11 Hours, 17 Minutes
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January 20 2021
  9 Hours, 38 Minutes
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January 20 2021
  9 Hours, 36 Minutes
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AMD EPYC 7601 2P 2021 Suite 1.0.0 System Test suite extracted from AMD EPYC 7601 2P 2021. pts/onednn-1.6.1 --matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/dav1d-1.7.1 -i summer_nature_1080p.ivf Video Input: Summer Nature 1080p pts/mnn-1.1.1 Model: inception-v3 pts/dav1d-1.7.1 -i chimera_8b_1080p.ivf Video Input: Chimera 1080p pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/openfoam-1.0.1 Motorbike 150 60 60 Input: Motorbike 30M pts/qe-1.0.2 ausurf.in Input: AUSURF112 pts/build-godot-1.0.0 Time To Compile pts/etcpak-1.0.0 --dxtc Configuration: DXT1 pts/rav1e-1.5.0 -s 10 -l 90 Speed: 10 pts/onednn-1.6.1 --matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU pts/mnn-1.1.1 Model: MobileNetV2_224 pts/rav1e-1.5.0 -s 1 -l 20 Speed: 1 pts/rav1e-1.5.0 -s 6 -l 60 Speed: 6 pts/lammps-1.3.2 in.rhodo Model: Rhodopsin Protein system/cryptsetup-1.0.1 PBKDF2-sha512 pts/mnn-1.1.1 Model: SqueezeNetV1.0 system/cryptsetup-1.0.1 AES-XTS 256b Encryption pts/lammps-1.3.2 benchmark_20k_atoms.in Model: 20k Atoms system/cryptsetup-1.0.1 PBKDF2-whirlpool system/cryptsetup-1.0.1 AES-XTS 256b Decryption system/cryptsetup-1.0.1 AES-XTS 512b Decryption pts/rav1e-1.5.0 -s 5 -l 60 Speed: 5 pts/lulesh-1.1.1 pts/unpack-firefox-1.0.0 Extracting: firefox-84.0.source.tar.xz system/cryptsetup-1.0.1 AES-XTS 512b Encryption pts/openfoam-1.0.1 Motorbike 300 120 120 Input: Motorbike 60M pts/dav1d-1.7.1 -i chimera_10b_1080p.ivf Video Input: Chimera 1080p 10-bit pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU pts/encode-opus-1.1.1 WAV To Opus Encode pts/onnx-1.0.1 super_resolution/super_resolution.onnx -e cpu Model: super-resolution-10 - Device: OpenMP CPU system/cryptsetup-1.0.1 Twofish-XTS 256b Encryption system/cryptsetup-1.0.1 Serpent-XTS 256b Encryption pts/encode-ogg-1.6.1 WAV To Ogg system/cryptsetup-1.0.1 Twofish-XTS 512b Decryption pts/tnn-1.0.1 -dt NAIVE -mp ../benchmark/benchmark-model/mobilenet_v2.tnnproto Target: CPU - Model: MobileNet v2 system/cryptsetup-1.0.1 Serpent-XTS 256b Decryption system/cryptsetup-1.0.1 Serpent-XTS 512b Encryption system/cryptsetup-1.0.1 Twofish-XTS 256b Decryption system/cryptsetup-1.0.1 Twofish-XTS 512b Encryption pts/amg-1.1.0 pts/encode-ape-1.4.0 WAV To APE system/cryptsetup-1.0.1 Serpent-XTS 512b Decryption pts/relion-1.0.1 --iter 1 --cpu --j 2 Test: Basic - Device: CPU pts/etcpak-1.0.0 -d Configuration: ETC1 + Dithering pts/encode-wavpack-1.4.1 WAV To WavPack pts/tnn-1.0.1 -dt NAIVE -mp ../benchmark/benchmark-model/squeezenet_v1.1.tnnproto Target: CPU - Model: SqueezeNet v1.1 pts/etcpak-1.0.0 Configuration: ETC1 pts/etcpak-1.0.0 --etc2 Configuration: ETC2 pts/synthmark-1.0.0 -tv -p100 -s30 Test: VoiceMark_100 pts/kripke-1.1.0 pts/onnx-1.0.1 model/test_shufflenetv2/model.onnx -e cpu Model: shufflenet-v2-10 - Device: OpenMP CPU pts/onnx-1.0.1 fcn-resnet101-11/model.onnx -e cpu Model: fcn-resnet101-11 - Device: OpenMP CPU pts/onnx-1.0.1 download_sample_10/bertsquad10.onnx -e cpu Model: bertsquad-10 - Device: OpenMP CPU pts/onnx-1.0.1 yolov4/yolov4.onnx -e cpu Model: yolov4 - Device: OpenMP CPU pts/mnn-1.1.1 Model: mobilenet-v1-1.0 pts/mnn-1.1.1 Model: resnet-v2-50 pts/dav1d-1.7.1 -i summer_nature_4k.ivf Video Input: Summer Nature 4K pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU pts/qmcpack-1.2.1 H2O/example_H2O-1-1 simple-H2O.xml Input: simple-H2O pts/cloverleaf-1.1.0 Lagrangian-Eulerian Hydrodynamics